A search engine that values depth over popularity

Hacker News

Hey HN, I'm excited to introduce Graphthem, a search engine designed to explore the deeper layers of knowledge rather than just surface-level popularity. While many AI search engines simply summarize top N results, we've found this approach often misses the many good stuff that is buried deeper in the links and references. Graphthem takes a different approach. we don't just look at the first few pages we find. We also dig into what those pages link to, so you get the whole story. This allows us to deliver answers that capture not just what's immediately visible, but also the foundational ideas and deeper insights that inform those results. Here's a comparison between Perplexity and Graphthem: Query 1: "most watched youtube videos?" Perplexity: https://www.perplexity.ai/search/most-watched-youtube-videos... Graphthem: https://graphthem.com/search?uuid=7f0839a9-85ee-4f81-a5c9-cb... - Query 2: "what is pagerank?" Perplexity: https://www.perplexity.ai/search/what-is-pagerank-ieJ.4iFqTq... Graphthem: https://graphthem.com/search?uuid=c689e9d1-d3d4-4d51-8602-00... --- Some related ideas I've explored before: https://news.ycombinator.com/item?id=35826540 https://news.ycombinator.com/item?id=35510949 I would love to hear your feedback. Please let us know how we can improve.

Visit product View on Hacker NewsDec 29, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, perplexity · Missing: mac, agents, macos

73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist

68%68% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

47%47% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: video, answers · Missing: mobile apps, ios, personal

31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: introduce · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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